11.90 FORECASTING MOVIE REVENUES WITH TWITTER. TWEETS Refer to the IEEE International Conference on Web Intelligence and Intelligent Agent Technology (2010) study of how social media (e.g., Twitter.com) may influence the products consumers buy, Exercise 11.279 (p. 642). Recall that opening weekend box-office revenue (in millions of dollars) and tweet rate (average number of tweets referring to the movie per hour) were collected for a sample of 23 recent movies. You fit a simple linear regression model, with y = revenue and x = tweet rate. The results are shown in the XLSTAT printout above. a. Evaluate the adequacy of the simple linear regression model. Do you recommend using the model for prediction purposes? b. Find a 95% prediction interval for the revenue (y) of a movie with a tweet rate (x) of 250 tweets per hour. Give a practical interpretation of the interval. XLSTAT Output for Exercise 11.9010 Regression of variable Revenue (millions): Goodness of fit statistics (Revenue (millions]]: Observations 23.0000 Sum of weight 23.0000 21.0000 0.8242 Adjusted R2 0.8159 MSE 177.3295 0.2093 Model parameters (Revenue (millions)): Source Value Standard error Pr > It] Lower bound Upper bound (95%) (95%) Intercept 1.1502 3.6761 0.3129 0.7575 -6.4947 8.7950 TweetRate 0.0788 0.0079 9.9233